I guess then it would be best to search the large microarray data repositories [?]Arrayexpress[?] and [?]GEO[?].

Kami,

You talked about R packages inlcuding multcomp. These packages often come with example datasets that you can use to get to grips with how the methods work. The dataset mtept from multcomp sounds like the sort of thing you're after (2 treatments, 4 endpoints)

library(multcomp)
data(mtept)
str(mtept)

#'data.frame':   111 obs. of  5 variables:
# $ treatment: Factor w/ 2 levels "Drug","Placebo": 2 2 2 2 2 2 2 2 2 2 ...
# $ E1       : int  4 5 1 4 3 4 2 2 3 2 ...
# $ E2       : int  3 0 0 0 0 1 0 2 0 0 ...
# $ E3       : int  3 1 1 3 2 2 4 5 1 1 ...
# $ E4       : int  5 7 9 5 9 6 6 5 7 9 ...

It doesn't have the patients split into two groups, but you can make that up:

grp <- as.factor(c(rep(c('one', 'two'), 50), 'two'))
head(grp)
# [1] one two one two one two
# Levels: one two

I want to use R in order to analyse the dataset; I think that arrays would be better.

Actually, anything may help, I have to try it in R. I am interested to give an example of how multiple hypothesis testing works so I don't mind what kind of dataset would be.

Also do you know where I can look for some examples of how we analyse datasets in R (regarding multiple hypothesis testing)? I have just find different packages like multtest, multcomp that apply in my case but still i need data to work on them.